class_docstr: Mean metric.
class_docstr_tok: ["Mean","metric","."]
docstr: Initializes mean metric.
  
  Args:
    feature_key_path: key path to feature to calculate the mean of.
    example_weights_key_path: key path to example weights.
    name: Metric base name.
docstr_tok: ["Initializes","mean","metric",".","Args",":","feature_key_path",":","key","path","to","feature","to","calculate","the","mean","of",".","example_weights_key_path",":","key","path","to","example","weights",".","name",":","Metric","base","name","."]
code: def __init__(
      self,
      feature_key_path: _KeyPath,
      example_weights_key_path: Optional[_KeyPath] = None,
      name: Optional[str] = None,
  ):
      """Initializes mean metric.
  
      Args:
        feature_key_path: key path to feature to calculate the mean of.
        example_weights_key_path: key path to example weights.
        name: Metric base name.
      """
      super().__init__(
          _mean_metric,
          feature_key_path=feature_key_path,
          example_weights_key_path=example_weights_key_path,
          name=name
          or f"{_MEAN_METRIC_BASE_NAME}_{'.'.join(feature_key_path)}",
      )
  
file_path: model-analysis/tensorflow_model_analysis/metrics/stats.py
imports: import dataclasses
  from typing import Any, Dict, Iterable, Optional, Tuple, Union
  import apache_beam
  from tensorflow_model_analysis.metrics import metric_types
  from tensorflow_model_analysis.utils import util
label_desc: Use image node_id 1 to create a new Mean object from inherited base classes: metric_types with example: obj = Mean(feature_key_path, example_weights_key_path, name)